Environmental Monitoring and Assessment

, Volume 133, Issue 1–3, pp 69–78 | Cite as

Biomonitoring of Environmental Pollution Using Dielectric Properties of Tree Leaves

Article

Abstract

In the present work, dielectric measurements were performed in plane-tree leaves collected from a polluted urban site and a natural unpolluted one, in order to investigate the sensitivity of dielectric relaxation spectroscopy to the detection of heavy metals pollution. Although heavy metal concentrations at the urban site are not found considerable higher than those at the natural site, the two samples exhibit different features in the recorded dielectric spectra. Evaluation of experimental data suggests that the dielectric modulus (M*(ω)) representation is the most suitable for accenting the different dielectric relaxation processes of each sample. The imaginary part of dielectric modulus M″(ω) was fitted using a three-term Havriliak–Negami relaxation function, with fitting parameters, which depend on the concentrations of heavy metals. The lower frequency relaxation process is attributed to the ionic conductivity of the samples, while the two others are due to different charge transport mechanisms of α-response. The investigation of plane-tree leaves in terms of their dielectric properties can be considered as a promising biomonitoring for environmental pollution.

Keywords

Biomonitoring Dielectric spectroscopy Heavy metals Leaves Pollution 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alaimo, M. G., Lipani, B., Lombardo, M. G., Orecchio, S., Turano, M., & Melati, M. R. (2000). The mapping of stress in the predominant plants in the city of Palermo by lead dosage. Aerobiologia, 16, 47–54.CrossRefGoogle Scholar
  2. Alfani, A., Baldantoni, D., Maisto, G., Bartoli, G., & Virzo De Santo, A. (1997). Time and site integrated biomonitoring of Pb, Cr, Fe, Cu, V and Cd in the urban area of Naples. Journal of Trace Elements in Medicine and Biology, 11, 176–178.Google Scholar
  3. Alfani, A., Baldantoni, D., Maisto, G., Bartoli, G., & Virzo De Santo, A. (2000). Temporal and spatial variation in C, N, S and trace element contents in the leaves of Quercus ilex within the urban area of Naples. Environmental Pollution, 109, 119–129.CrossRefGoogle Scholar
  4. Alfani, A., Bartoli, G., Rutigliano, F. A., Maisto, G., & Virzo De Santo, A. (1996). Trace metal biomonitoring in the soil and the leaves of Quercus ilex in the urban area of Naples. Biological Trace Element Research, 51, 117–131.CrossRefGoogle Scholar
  5. Alfani, A., Maisto, G., Iovieno, P., Rutigliano, F. A., & Bartoli, G. (1996). Leaf contamination by atmospheric pollutants as assessed by elemental analysis of leaf tissue, leaf surface deposit and soil. Journal of Plant Physiology, 148, 243–248.Google Scholar
  6. Broadhurst, M. G., Chiang, C. K., Wahlstrand, K. J., Hill, R. M., Dissado, L. A., & Pugh, J. (1987). The dielectric properties of biological tissue (crassula portulacea) from 10−2 to 109 Hz. Journal of Molecular Liquids, 36, 65–73.CrossRefGoogle Scholar
  7. Czuba, M., & Kraszewski, A. (1994). Long-term cadmium exposure accelerates oxidant injury: significance of bound/free water states during long-term metal stress. Ecotoxicology and Environmental Safety, 29, 330–348.CrossRefGoogle Scholar
  8. Donth, E. (1992). Relaxation and thermodynamics in polymers. Berlin: Akademie Verlag.Google Scholar
  9. Elliott, S. R. (1994). Use of the modulus formalism in the analysis of ac conductivity data for ionic glasses. Journal of Non-Crystalline Solids, 170, 97–100.CrossRefGoogle Scholar
  10. Frohlich, H. (1958). Theory of dielectrics. Oxford: Clarendon.Google Scholar
  11. Georgeaud, V. M., Rochette, P., Ambrosi, J. P., Vandamme, D., & Williamson, D. (1997). Relationship between heavy metals and magnetic properties in a large polluted catchment: the Etang de Berre (south of France). Physics and Chemistry of Earth, 22, 211–214.CrossRefGoogle Scholar
  12. Granier, L., & Chevreuil, M. (1992). On the use of tree leaves as bioindicators of the contamination of air by organochlorines in France. Water, Air and Soil Pollution, 64, 575–584.CrossRefGoogle Scholar
  13. Havriliak, S., & Negami, J. (1966). A complex plane analysis of α-dispersions in some polymer systems. Journal of Polymer Science, C14, 99–117.Google Scholar
  14. Hill, R. M., Dissado, L. A., & Pathmanathan, K. (1987). The low-frequency dielectric properties of leaves. Journal of Biological Physics, 15, 2–16.CrossRefGoogle Scholar
  15. Hill, R. M., Dissado, L. A., Pugh, J., Broadhurst, M. G., Chiang, C. K., & Wahlstrand, K. J. (1986). The dielectric response of portulacaceae (Jade) leaves over an extended frequency range. Journal of Biological Physics, 14, 133–135.CrossRefGoogle Scholar
  16. Jonscher, A. K. (1983). Dielectric relaxation in solids. London: Chelsea Dielectrics.Google Scholar
  17. Jonscher, A. K. (1999). Dielectric relaxation in solids. Journal of Physics D: Applied Physics, 32, R57–R70.CrossRefGoogle Scholar
  18. Kaya, A. (2001). Electrical spectroscopy of kaolin and bentonite slurries. Turkish Journal of Engineering and Environmental Sciences, 25, 345–354.Google Scholar
  19. Kaya, A., & Fang, H.-Y. (1997). Identification of contaminated soils by dielectric constant and electrical conductivity. Journal of Environmental Engineering, 123(2), 169–177.CrossRefGoogle Scholar
  20. Kremer, F., & Schönhals, A. (Eds.) (2002). Broadband dielectric spectroscopy. Springer, Berlin Heidelberg New York.Google Scholar
  21. Lux, F. (1993). Models proposed to explain the electrical conductivity of mixtures made of conductive and insulating materials. Journal of Materials Science, 28, 285–301.CrossRefGoogle Scholar
  22. Luyssaert, S., Raitio, H., Vervaeke, P., Mertens, J., & Lust, N. (2002). Sampling procedure for the foliar analysis of deciduous trees. Journal of Environmental Monitoring, 4, 858–864.CrossRefGoogle Scholar
  23. Maisto, G., Baldantoni, D., De Marco, A., Alfani, A., & Virzo De Santo, A. (2003). Biomonitoring of trace element air contamination at sites in Campania (Southern Italy). Journal of Trace Elements in Medicine and Biology, 17, 51–55.CrossRefGoogle Scholar
  24. Matzka, J., & Maher, B. A. (1999). Magnetic biomonitoring of roadside tree leaves: identification of spatial and temporal variations in vehicle-derived particulates. Atmospheric Environment, 33, 4565–4569.CrossRefGoogle Scholar
  25. Moreno, E., Sagnotti, L., Diranès-Turell, J., Winkler, A., & Cascella, A. (2003). Biomonitoring of traffic air pollution in Rome using magnetic properties of tree leaves. Atmospheric Environment, 37, 2967–2977.CrossRefGoogle Scholar
  26. Muxworthy, A., Schmidbauer, E., & Petersen, N. (2002). Magnetic properties and Mössbauer spectra of urban atmospheric particulate matter: a case study from Munich, Germany. Geophysical Journal International, 150, 558–570.CrossRefGoogle Scholar
  27. Piczak, K., Leśniewicz, A., & Zyrnicki, W. (2003). Metal concentrations in deciduous tree leaves from urban areas in Poland. Environmental Monitoring and Assessment, 86, 273–287.CrossRefGoogle Scholar
  28. Roldughin, V. I., & Vysotskii, V. V. (2002). Percolation properties of metal-filled polymer films, structure and mechanisms of conductivity. Progression in Organic Coatings, 39, 81–100.CrossRefGoogle Scholar
  29. Rowe, R. K., Shang, J. Q., & Xie, Y. (2001). Complex permittivity measurement system for detecting soil contamination. Canadian Geotechnology Journal, 38, 498–506.CrossRefGoogle Scholar
  30. Rusiniak, L. (1998). Dielectric constant of water in a porous rock medium. Physics and Chemistry of the Earth, 23, 1133–1139.CrossRefGoogle Scholar
  31. Saltas, V., Vallianatos, F., Soupios, P., Makris, J. P., & Triantis, D. (2006). Dielectric and conductivity measurements as proxy method to monitor contamination in sandstone. Journal of Hazardous Materials (in press). DOI: http://dx.doi.org/10.1016/j.jhazmat/2006.08.051
  32. Schaumburg, G. (1999). New integrated dielectric analyzer extends accuracy and impedance range for material measurements. Dielectrics Newsletters, 11. Retrieved from http://www.novocontrol.de/newsletter/dnl11.pdf (May).
  33. Schlosse, E., Schönhals, A., Carius, H.-E., & Goering, H. (1993). Evaluation method of temperature-dependent relaxation behavior of polymers. Macromolecules, 26, 6027–6032.CrossRefGoogle Scholar
  34. Schwann, H. P. (1957). Electrical properties of tissue and cell suspensions. Advances in Biology and Medical Physics, 5, 147–209.Google Scholar
  35. Shang, J. Q., Ding, W., Rowe, R. K., & Josic, L. (2004). Detecting heavy metal contamination in soil using complex permittivity and artificial neural networks. Canadian Geotechnology Journal, 41, 1054–1067.CrossRefGoogle Scholar
  36. Swaileh, K. M., Hussein, R. M., & Abu-Elhaj, S. (2004). Assessment of heavy metal contamination in roadside surface soil and vegetation from the West Bank. Archives of Environment Contamination and Toxicology, 47, 23–30.CrossRefGoogle Scholar
  37. Urbat, M., Lehndorff, E., & Schwark, L. (2004). Biomonitoring of air quality in the Cologne conurbation using pine needles as a passive sampler. Part I. Magnetic properties. Atmospheric Environment, 38, 3781–3792.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  • V. Saltas
    • 1
  • D. Triantis
    • 2
  • T. Manios
    • 3
  • F. Vallianatos
    • 1
  1. 1.Department of Natural Resources and EnvironmentTechnological Educational Institute of CreteChania, CreteGreece
  2. 2.Materials Research Laboratory, Department of ElectronicsTechnological Educational Institute of AthensAthensGreece
  3. 3.School of Agricultural TechnologyTechnological Educational Institute of CreteChania, CreteGreece

Personalised recommendations